



"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional

from seqaseq_trainer import arg_to_scheduler

from transformers import TrainingArguments


SCREAMING_SNAKE_CASE_      						=			logging.getLogger(__name__)




@dataclass
class       snake_case_    (    _lowerCAmelCase					):
							__lowerCAmelCase            =       field(
							    default=0.0  ,metadata={"help": "The label smoothing epsilon to apply (if not zero)."}					)
							__lowerCAmelCase            =       field(default=_lowerCAmelCase  ,metadata={"help": "Whether to SortishSamler or not."}					)
							__lowerCAmelCase            =       field(
							    default=_lowerCAmelCase  ,metadata={"help": "Whether to use generate to calculate generative metrics (ROUGE, BLEU)."}					)
							__lowerCAmelCase            =       field(default=_lowerCAmelCase  ,metadata={"help": "whether to use adafactor"}					)
							__lowerCAmelCase            =       field(
							    default=_lowerCAmelCase  ,metadata={"help": "Encoder layer dropout probability. Goes into model.config."}					)
							__lowerCAmelCase            =       field(
							    default=_lowerCAmelCase  ,metadata={"help": "Decoder layer dropout probability. Goes into model.config."}					)
							__lowerCAmelCase            =       field(default=_lowerCAmelCase  ,metadata={"help": "Dropout probability. Goes into model.config."}					)
							__lowerCAmelCase            =       field(
							    default=_lowerCAmelCase  ,metadata={"help": "Attention dropout probability. Goes into model.config."}					)
							__lowerCAmelCase            =       field(
							    default="linear"  ,metadata={"help": f"""Which lr scheduler to use. Selected in {sorted(arg_to_scheduler.keys()					)}"""}  ,)




import numpy as np







def  lowerCAmelCase_	(lowerCAmelCase__:		np.ndarray		,						lowerCAmelCase__:		float  ):





			"""simple docstring"""


			return np.where(vector > 0		,						lowerCAmelCase__		,						(alpha * (np.exp(lowerCAmelCase__  ) - 1))  )


if __name__ == "__main__":
	import doctest

	doctest.testmod()






